Factors affecting the young vietnamese customers willingness to participate in fashion

The questionnaire including demographic questions, behavioral intention, attitude toward behavior, subjective norm, perceived behavioral control, perceived usefulness, perceived ease of

VIETNAM NATIONAL UNIVERSITY, HANOI

VIETNAM NATIONAL UNIVERSITY, HANOI

INTERNATIONAL SCHOOL

GRADUATION PROJECT

FACTORS AFFECTING THE YOUNG VIETNAMESE

CUSTOMERS’ WILLINGNESS TO PARTICIPATE IN

FASHION RENTALS

SUPERVISOR: MBA Pham Huong Trang STUDENT: Nguyen Thi Thoa

STUDENT ID: 16071115 COHORT: IB2016A

MAJOR: International Business

Hanoi, Year 2020

in this project are clearly cited according to regulations

I take full responsibility for the fidelity of the number and data and other contents of

my graduation project

Hanoi, 25th May 2020

Thoa Nguyen Thi Thoa

ACKNOWLEDGEMENT

First of all, I would like to express my deep thankfulness to my supervisor, MBA Pham Huong Trang who inspired me to do this study, guided me how to make it done properly, and spent time on helping me to correct it during last time Without her enthusiasm, great passion and useful comments, I might not complete this paper within a limited time frame

I also would like to express the sincerest gratitude to all the lecturers and professors

of International School- Vietnam National University, who gave me the necessary knowledge about international business and other majors during four years I studied here That helped me a lot when I conducted this research

Besides, I would like to say thank you to all the participants who helped me answering the questionnaire so that I can get data to do the study I really appreciated those who spent time on helping me completing the survey

Also, I would like to send my sincere gratitude to my families and friends for their unconditional love, perseverance, encouragement and emotional support Without them, I might not feel strong enough to finish the research

Finally, I wish all the best will come to my supervisor and all the lecturers and professors of International School- Vietnam National University Wish everyone will have more happiness in life and more success in career

Thank you all very much!

Student, Nguyen Thi Thoa

TABLE OF CONTENT

TABLE OF CONTENT 1

TABLE OF NOTATIONS AND ABBREVIATIONS 4

LIST OF TABLE 5

LIST OF FIGURE 6

ABSTRACT 1

CHAPTER 1: INTRODUCTION 3

1.1 Background of the study 3

1.2 The prior studies and Research gap 7

1.3 Research objectives and Research questions 8

1.4 Research method 9

1.5 Research findings 9

1.6 Structure of the study 10

CHAPTER 2: LITERATURE REVIEW 11

2.1 The sharing economy and the online fashion rental service 11

2.1.1 The basic knowledge related to sharing economy 11

2.1.2 The online fashion rental service 14

2.2 The characteristics of generation Z (gen Z) 17

2.3 Theory of planned behavior (TPB) 18

2.4 Technology acceptance model (TAM) 20

2.5 The framework and the research hypotheses 21

2.5.1 Perceived usefulness 22

2.5.2 Perceived ease of use 22

2.5.3 Interpersonal influence 23

2.5.4 Electronic word of mouth (E-WOM) credibility 24

2.5.5 Influencer marketing (KOLs) 25

2.5.6 Attitude toward behavior 25

2.5.7 Subjective norms 26

2.5.8 Perceived behavioral control 27

2.5.9 Behavioral intention 28

CHAPTER 3: RESEARCH METHODOLOGY 29

3.1 Research procedure 29

3.2 Survey as a quantitative research method 30

3.3 Questionnaire design and pilot test 30

3.3.1 Definition of items 30

3.3.2 Designing questionnaire 31

3.3.3 Pilot test 35

3.4 Sample size and data collection 35

3.5 Analyzing Data Plan 36

3.5.1 Reliability analysis by Cronbach’s alpha 36

3.5.2 Exploratory Factor Analysis (EFA) 37

CHAPTER 4: DATA ANALYSIS AND FINDINGS 40

4.1 Descriptive statistics 40

4.1.1 Respondents’ characteristic 40

4.1.2 Mean- Analysis 42

4.2 Reliability Analysis by Cronbach’s alpha 44

4.2.1 Reliability of perceived usefulness- PU scale 45

4.2.2 Reliability of perceived ease of use- PEU scale 45

4.2.3 Reliability of Interpersonal influence- II scale 46

4.2.4 Reliability of E-WOM credibility – EC scale 46

4.2.5 Reliability of Influencer marketing- IM scale 46

4.2.6 Reliability of Attitude toward behavior- AB scale 46

4.2.7 Reliability of Subjective norm- SN scale 47

4.2.8 Reliability of Perceived behavioral control- PBC scale 47

4.2.9 Reliability of Behavioral intention- BI scale 47

4.3 Exploratory Factor Analysis 48

4.4 Confirmatory Factor Analysis (CFA) 51

4.5 Structural equation modeling (SEM) 55

4.6 Bootstrapping and Hypotheses tested results 58

CHAPTER 5: DISCUSSIONS, CONCLUSIONS AND LIMITATIONS 60

5.1 Discussions 60

5.2 Contribution of the research 63

5.3 Limitations and suggestions for future research 64

REFERENCES 65

APPENDIX 1: QUESTIONNAIRE (English version) 81

APPENDIX 2: QUESTIONNAIRE (Vietnamese version) 86

APPENDIX 3: THE PRIOR STUDIES 1 90

APPENDIX 4: THE PRIOR STUDIES 2 92

TABLE OF NOTATIONS AND ABBREVIATIONS

In the research, these letters are abbreviated to easy follow The below table would

be described in detail

LIST OF TABLE

Table 1: The definition of variables 31

Table 2: Demographic information of respondents 32

Table 3: Five-point Likert scale 33

Table 4: Measuring items for questionnaire 33

Table 5: The rule of alpha value 37

Table 6: The using of factor loadings 38

Table 7: The acceptance level of Model fit 39

Table 8: The distribution of respondents‘ characteristic 40

Table 9: Descriptive statistics of 375 observations 43

Table 10: Reliability Analysis 44

Table 11: KMO and Bartlett‘s Test 48

Table 12: The Pattern Matrix 49

Table 13: Model fit summary 51

Table 14: Standardized Regression Weights 52

Table 15: the value of CR and AVE 54

Table 16: The value of AVE and MSV 54

Table 17: Regression Weights 56

Table 18: Standardized Regression Weights 57

Table 19: The order of factor‘s effect on variables 57

Table 20: Bootstrapping with sample size N= 1000 58

Table 21: Hypotheses Tested Results 58

LIST OF FIGURE

Figure 1: Proposed Research Model 21

Figure 2: Research procedure 29

Figure 3: The measurement model 51

Figure 4: The structural model 55

ABSTRACT

Purposes: To reduce the damaging effects of fast fashion, fashion rental is

becoming the global trend and potential business model which brings many benefits

to both customers and providers Therefore, the studies on this field are very necessary and meaningful, which will receive a lot of attention Combining the Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM), this study investigates the determinants of young Vietnamese consumers‘ intention to using online fashion rental service Specifically, the research focuses on a group of subjects who were born after 1995, called generation Z Based on the outstanding characteristics of this group, the paper offers new hypotheses compared to other prior studies in the same field In particular, it specifies the effects of two variables: electronic- word of mouth (E-WOM) credibility and influencer marketing on subjective norm

Design/Methodology/Approach: The research uses survey as a quantitative

method The questionnaire including demographic questions, behavioral intention, attitude toward behavior, subjective norm, perceived behavioral control, perceived usefulness, perceived ease of use, interpersonal influence, E-WOM credibility and influencer marketing was developed and delivered online to 375 people After that, the SPSS26 and AMOS20 were used to analyze the collected data

Findings: This study contributes to the extant literature concerning factors

impacting the willingness of customer to participate in fashion rental Firstly, the results show that attitude toward behavior, subjective norm and perceived behavioral control have positive and significant relationships with behavioral intention of people It emphasizes that behavioral intention can be most strongly influenced by each individual‘s ability in relation to resources, such as: time, money Secondly, the positive relationships between attitude and two other factors: perceived usefulness and perceived ease of use are also highlighted In which,

usefulness Lastly, all three elements: interpersonal influence, E-WOM credibility, and influencer marketing have positive impacts on subjective norm Influencer marketing has the highest level of effect compared with the two remaining variables

Implications: The research findings help to understand factors that might influence

customers‘ intention to rent the clothes online in Vietnam From there, it is useful for managers, or marketers to catch the key predictors of customers‘ behavioral intention Besides, this provides basic knowledge related to sharing economy, online fashion rental, generation Z with empirical evidence that can be taken into considerations in the business strategies

Originality/value: This study focuses on gen Z which is the most potential group

of customers Besides, the study expands the TPB model by exploring the impacts

of other dimensions of subjective norm namely E-WOM credibility and influencer marketing

Key words: fashion rental/ online renting clothes, generation Z, sharing economy,

TPB model, TAM model, behavioral intention, attitude toward behavior, subjective norm, perceived behavioral control, perceived usefulness, perceived ease of use, interpersonal influence, E-WOM credibility, and influencer marketing

CHAPTER 1: INTRODUCTION

In the Vietnam context, fashion rental service has appeared for a long time, but it

is limited to some types of costumes such as wedding or dancing dress and in the form of store shopping Hence, the online renting clothes is still quite new to Vietnamese customers Besides, by 2025, Generation Z , who were born after

1995, will account for about 25% of the national workforce, and are equivalent to about 15 million potential consumers (Nielsen, 2018) The report of Nielsen also shows that this group of people likes to experience new services or new trends, and they have a higher awareness of online services as well as social issues Therefore, this research not only shows the potential of a special type of fashion - clothing rental service in Vietnam, but also emphasizes the key factors that influence the Vietnamese younger customer’s decision to experience online hiring

This chapter consists of five sections Initially, the chapter elaborates background for the study (section 1.1) before the prior studies and research gaps are presented (section 1.2) Subsequently, the research objectives and research questions are emphasized (section 1.3) After that, a brief description of the research methods is provided (section 1.4), which is followed by a presentation of research findings (section 1.5) The chapter closes with a presentation of the thesis structure (section 1.6)

1.1 Background of the study

In recent years, sharing economy is a popular topic among companies and academic researchers It is defined that people share their intangible assets and underutilized tangible assets for money or for free with the help of the Internet and online platforms (Görög, 2018) A decade ago, in a world where Airbnb had not changed the tourism industry, sleeping in strangers' houses rather than in a well-known hotel would have considered a little dangerous Before Uber, or Grab dominated the

transportation, getting into a stranger's car might have unprecedented It can be seen that, the sharing economy is gradually replacing the ownership economy, becoming

a potentially profitable business model in all fields (Tu and Hu, 2018) Sharing economy is also known as collaborative consumption, which is expected to diminish social problems, such as poverty, excessive consumption of resources, and environmental pollution Therefore, some authors are trying to research and expect positive effects of sharing economy on the fashion industry - one of the most

polluting industries in the world (Armstrong et al., 2016; Yoon and Kim, 2017;

Iran, 2018; Lang and Joyner Armstrong, 2018; Tu and Hu, 2018; Lee and Chow, 2020)

Although fashion rental is not a new phenomenon, an increase in environmental concerns has made hiring clothes more popular than ever, leading to a global trend According to a report of damaging parliamentary committee, the textile industry discharges 1.2bn tons of CO2 per year, and is responsible for the consumption of huge quantities of water, while 35% of the microplastics in the ocean come from the synthetic fibres in abandoned clothing (PerfectSourcing, 2019) Therefore, fast fashion is assessed as the second dirtiest industry, only coming in behind the oil industry in terms of pollution (AlterNet, 2015) Although the perception of people about negative impacts of fast fashion is increasing by education, or propaganda, the actual demand for shopping shows no sign of slowing down The research of Hubbub Foundation suggests that one in six young people say they do not feel able

to wear an outfit again once it has appeared on social networking sites Morley, 2017) And, nearly half of young women participants feel like wearing different clothes every time they go out As the dark side of fast fashion is quickly being exposed to the world and the demand is constantly increasing, the awareness

(Cart-of sharing "wardrobes" makes important sense for the planet's sake, especially environmental protection (AlterNet, 2015) Based on the principle of sharing economy, renting clothes would be an effective solution that brings many benefits

in terms of sustainability fashion, such as maximizing usage and reducing the

impact of goods that were discarded after limited use (Rachel Botsman and Rogers, 2010) Moreover, It is not only an eco-friendly option, but also brings economic benefits to customers as sharing the cost of products and reducing the burden of ownership (Rachel Botsman and Rogers, 2010; Lang and Joyner Armstrong, 2018; Lang, Li and Zhao, 2019)

This study classifies clothing rental into two categories based on the types of sharing economy, brand-to-consumer and peer-to-peer Firstly, for brands-to-consumer model, the fashion firms offer list of service packages with a fixed monthly price, and customers who participate in this service package will have unlimited rights to hire clothing products in corresponding catalogs Such as: The United States is currently the leader of fashion rental industry, specifically Rent the Runway company, which began operating in 2009, provides one month's subscription cost of 160$ A United Kingdom company has also started this service with a monthly cost of 100$ Other brands like Mang Walk, My Wardcoat HQ and Front Row, H&M provide rental service for their premium designs and luxury products on a monthly subscription cost plus rental fee per item, typically ranging from 10% to 15% of the selling price Secondly, for peer-to-peer model, each individual can join in both the provision and use of the service, making own agreements on costs or transport For example: Merri Smith and Violet Gross launched their startup- Tulerie, which is the wardrobe rental platform business They look for women interested in both borrowing and lending, resulting that roughly 80 percent of platform's members are active on both sides of rental equation (Biins, 2019) Therefore, Tulerie not only helps members rent and earn money on their wardrobes but it gives them a way to offload items that no longer have any place in their closets

In addition to the transformation in fashion trends, the customers' shopping habits are also gradually shifting from store shopping to online shopping Advances in e-commerce technology have made online fashion renting more convenient and accessible, creating favorable conditions for development of this service (Cart-

Morley, 2017) In fact, the online fashion rental market has recently been expanding exponentially in many countries, for examples: Girl Meets Dress in the U.K., Rent the Runway in the U.S., Meilizu in China, Lend My Trend, and HUMM (Gullstrand

Edbring, Lehner and Mont, 2016; Lai et al., 2018) According to a report of

Technavio organization in 2019, the potential development of this service is enormous, when it only accounted for 1% of the fashion market but the growth rate reached 9.98% (Technavio, 2019) Allied Market Research also found that the global clothing rental market was valued at approximately $1015 million in 2017 and is estimated to reach $1,856 million by 2023 (Iqbal, 2017)

The focal point of this study is generation Z which is the group of people who were born after 1995 with the high level of education, information technology, and innovation (Priporas, Stylos and Fotiadis, 2017) There are some reasons why the study chooses gen Z to analyze Firstly, It is the youngest and largest consumer group across all generations from 2017 to 2030 (Priporas, Stylos and Kamenidou, 2019) Gen Z is considered as the main potential consumer group of companies in many fields, especially technology, entertainment activities or fashion industry (Bassiouni and Hackley, 2014) A report conducted by Barclays bank in 2018 identified that gen Z plays a key role in the future economic development, because they can represent 40% of consumers in the United States, Europe and BRIC (Brazil, Russia, India and China) by 2020 Secondly, gen Z is the first group of people who were born into a digital world, they live online and are heavy users of technology (Bernstein, 2015) Therefore, they have a high awareness of online trading and easily take advantage of online resources to evaluate products before shopping Lastly, A research identified that Gen Z is characterized as economically conservative and social activists (Barclay, 2015) These people not only think about personal satisfaction, but also are more sensitive to social impacts (Abdullah, Mahadee Ismail and Albani, 2018) Therefore, this research will focus on surveyed participants – gen Z to shed light on the factors that influence this group's behavior regarding fashion rental trends

1.2 The prior studies and Research gap

The studies on human behavior have resulted in a multitude of theories and assumptions with many arguments from psychologists and researchers (Martin Luenendonk, 2017) Not all people react in the same way, or behave in the same manner, even under the exact same situation There are various factors which impact behavior of people Those are what psychologists and thinkers have been trying to study and make sense of in the past few decades (Martin Luenendonk, 2017) In terms of human behavior, behavioral intention also becomes an interesting topic It refers to the tendency for which a person wants to take a specific action Theory of planned behavior is the most popular model that is used to analyze factors affecting behavioral intention It is adopted in many fields and previous

researches: education (Knauder and Koschmieder, 2019; Rana et al., 2019), health (Lee et al., 2016; Gabriel, Hoch and Cramer, 2019), transportation (Cristea and Gheorghiu, 2016; Potard et al., 2018) In this study, related to fashion field, factors

affecting the behavioral intention to engage in renting clothes will be explored and identified

Although the trend of hiring clothes is getting more attention in the world, the number of studies on this topic is still low and limited compared to other topics regarding behavioral intention research In which, most studies focused on exploiting factors that affect customers‘ behavior, based on the main TPB theoretical model and incorporating a number of other theoretical foundations, such

as IDT, VBN, EVA or TRA (Iran, 2018; Tu and Hu, 2018; Lee and Chow, 2020) The results of these studies show that attitude and subjective norms are the main factors to predict customers‘ intention to engage in fashion rental, especially online service Following this motive, the paper continues to build a research model, based

on the TPB and TAM theory, to deeply measure the influence and relationship among variables that shape customers' behavior

Besides, there are two gaps in previous studies that will be improved in this article Firstly, in prior researches, the authors often focused on analyzing variables related

to attitudes such as compatibility, relative advantage, personal innovation, ecological importance, or psychological ownership (Becker-Leifhold, 2017; Tu and

Hu, 2018; Lee and Chow, 2020) Meanwhile, only interpersonal or social influence

of subjective norms that are associated with relative's opinion, friend's suggestion or worth of mouth review has been highlighted into relationship with customers' intention (Becker-Leifhold, 2017; Tu and Hu, 2018) Hence, in this study, the influence of factors, in term of subjective norms, will be explored further to provide deep understanding about young customers‘ intention Secondly, another limitation of previous researches is relative to the surveyed participants, lacking of

concentration (Armstrong et al., 2016; Becker-Leifhold, 2017; Tu and Hu, 2018;

Lee and Chow, 2020) The Vietnamese younger- gen Z is the main targeted group in this study This is a group of potential customers with outstanding characteristics related to technology application, personal awareness and social responsibility (Abdullah, Mahadee Ismail and Albani, 2018) For those living in the world of social networking, besides effecting from friends or relatives source, customers may

be governed by large sources of information on the internet or marketing channels Therefore, subjective norm is determined in the relation and impact of interpersonal influence, electronic- word of mouth and influencer marketing

1.3 Research objectives and Research questions

This study contributes to the extant knowledge concerning factors impacting customers‘ willingness to participate in fashion rental through the following research objectives:

- To clarify the relationship and impact of attitude, subjective norms, and perceived behavioral control on the behavioral orientation of young customers following the TPB and TAM theory

- To expand and provide more knowledge related to fashion rental trends and characteristics of gen Z, helping business companies have more information to analyze and apply in real activities

- To demonstrate the influence of E-WOM and influencer marketing on generation

Z engagement in hiring clothes

In order to achieve these objectives, two research questions are addressed as follows:

1 Why does the fashion rental in terms of sharing economy become a potential business model?

2 What are the main factors affecting the Vietnamese younger customers’ willingness to engage in fashion rental service?

1.4 Research method

A questionnaire survey is employed to investigate the impacts of factors based on TPB theoretically model SPSS and AMOS – SEM are adopted to analyze the quantitative data obtained from 375 young participants in Vietnam These applications enable the data to be sequentially analyzed via the measurement model and structural model The former enables reliability and validity of constructs‘ measures are assessed while the later is used for testing hypotheses of the study

1.5 Research findings

Applying TPB model, the study confirms the effects of three factors: attitude toward behavior, subjective norm, and perceived behavioral control on the behavioral intention of young customers to participate in renting fashion In which, the strongest influence comes from the perceived behavioral control, regarding ability

to hire clothes after assessing the personal resources Moreover, the highlight of this study is to focus on the Vietnamese young customers- generation Z who are affected by using technology and social networks Therefore, combining the TAM model, the results show the positive relationships between perceived usefulness,

perceived ease of use and attitude toward behavior Besides, in terms of subjective norm, all three factors interpersonal influence, E-WOM credibility, and influencer marketing have significant relationship with subjective norm Especially, influencer marketing plays an important role that makes stronger impacts on subjective norm than the remaining two variables

1.6 Structure of the study

The research project is organized in 5 chapters Chapter 1, present chapter provides the background for the study, prior studies and research gaps, research objectives and research questions, research methods, research finding and the structure of the study Chapter 2 reviews literature on necessary knowledge about fashion rental service in sharing economy trend, the information related to potential group of customers- gen Z, and factors shaping customers‘ engagement Chapter 3 states the selected research method of study, which describe a comprehensive research procedure of the survey design Chapter 4 presents technique of data analysis and research findings The study closes with chapter 5 where the research findings are discussed and the research conclusion is drawn Also, the limitations of the study are addressed and suggestions for the future research are provided

CHAPTER 2: LITERATURE REVIEW

This chapter aims to understand the sharing economy, online fashion rental service and generation Z (section 2.1 and 2.2) before providing theoretical perspective on factors impacting customers‘ behavioral intention (section 2.3 and 2.4) Then, the conceptual framework and the proposed hypotheses are shown in section 2.5

2.1 The sharing economy and the online fashion rental service

2.1.1 The basic knowledge related to sharing economy

The sharing economy has increasingly concerned and received significant attention from scholars, and policymakers, as well as individuals in recent years Sharing economy can be labeled with various names, and it overlaps considerably with other concepts, such as the collaborative economy, collaborative consumption, access economy, platform economy, and community-based economy (Belk, 2014)

Sharing economy is originated from the collaborative consumption idea proposed

by Felson and Spaeth (1978) through peer-to-peer platforms or markets It is considered as a consumption behavior mode using exchanges, sharing, bartering, transaction, and leasing (Möhlmann, 2015) Sharing may be not new concept, but sharing economy driven by the Internet and other supporting tools or features is a recent phenomenon (Belk, 2014) Heinrichs (2013) suggested that the drivers of the sharing economy include social media and information technology that allow the online interaction Hence, the dominant platform of the sharing economy has been online websites A number of online-service companies pioneering the sharing economy include e-Bay, Craiglist, Napster, Wikipedia, YouTube, and Ask.com Economic, societal and technological drivers (Owyang, 2014) promote the innovative forms of collaborative consumption, leading the appearance of more and more applications in the public, private, non-profit and profit sector (Toni, Renzi and Mattia, 2017)

In addition, the collaborative economy which is a new potential business model has

transaction and product exchange are the main differences of sharing economy compared with other business models Some authors argue that sharing economy consists of three key cores: access economy, platform economy, and community-based economy (Acquier, Daudigeos and Pinkse, 2017) It is not only considered in business-to-consumer rental , but also allowed to expand into the consumer-to-

consumer environment (Rim Choi et al., 1998)

The main characteristic of sharing economy is the possibility of using goods and services by paying for the temporary experience , with no transfer of ownership taking place (Bardhi and Eckhardt, 2012) Many economic, spatial and temporal advantages derive from using rather than owning goods Moreover, it also brings positive impacts on the sustainable development activities, such as reducing negative impact on environment, saving energy and reducing carbon, allowing people to have products they cannot afford In order to promote sustainability, consumers need to decrease their level of consumption (Pogutz and Micale, 2011) The adoption of collaborative economy models on a large scale and vary fields by companies as well as in the consumption activities of individuals is considered a very promising way of making production and consumption more sustainable

(Liedtke et al., 2015) Chiu (2014) emphasized that there are many reasons for

development of sharing economy, such as economic downturn, rise of environmental awareness, and popularity of social media and other factors In combination with this trend, companies can create online rental services and take environmental protection or resource utilization as main factors to communicate with customers

The sharing economy can be classified into three categories: product-service systems, redistribution markets, and collaborative lifestyles by Rachel, Botsman and Rogers (2010) Firstly, product-service systems mean that owners of certain products or services share their products or services with others by way of a fee-based rental Instead of purchasing, consumers can experience services or enjoy the benefits of products by leasing Some multiple emerging platforms have invested in

this sharing services, such as Zipcar, Lyft and other car sharing, Airbnb rent sharing services Secondly, in terms of redistribution markets, families often have a large number of rarely used and idle assets that could only be placed in storage rooms or discarded in the past Nowadays, by using internet, these second-hand products are redistributed on online platforms rapidly to those people in need The appearance

of SwapTree, eBay, Freecycle and other second-hand exchanges, sales, or recycling platforms allow people to save resources and protect environment Thirdly, related

to collaborative lifestyles, it means that various interests and common needs of consumer may gather on social platforms to share or exchange relatively recessive assets From there, it helps idle resources create greater utility, for examples time, money, experience, and space, through peer-to-peer lending platform, Zopa, Lending Club or rental services such as Airbnb

Based on the great benefits, at present, the sharing economy is growing continuously in all fields and countries For examples: one report in 2018 of China forecasted an annual growth rate of 30 percent or more over the next three years for sharing economy, ―thanks to the public‘s active participation, government policy support and mature business mode‖ Besides, the number of consumers taking part

in China‘s sharing economy increased by 7.1 percent compared with 2017 (SMEBIZ, 2019) In this country, bicycles were among the top sharing products, with 91 percent of those open to collaborative consumption trend saying they had rented or bought second-hand bicycles For cars, it was 61 percent Books and consumer electronics were far behind transportation when it came to a willingness

to take part in the sharing economy, at about 25 percent for both product categories (PYMNTS, 2019) According to a survey conducted by PWC in 2017, it was estimated that the sharing economy in Europe would experience exponential growth from the current € 28 billion to € 570 billion (Bolassa, 2017) In other words, all sectors may increase in value 20 times in the next 10 years The analysis also predicted that 85% of all receipts will favor micro-entrepreneurs who work with on-line platforms At the Vietnamese conference held in 2018, some experts

identified that Vietnam is positioned to take advantage of the growing opportunities presented by the sharing economy Rebecca Bryant, Australian Embassy Charge D‘Affaire, said that ― with a well-educated and young population and almost 70 percent of people owning a smart-phone‖, Vietnam‘s economy stood to benefit significantly from these developing technologies (VietNamNews, 2018) By this business trend, consumers can take advantages because the market would become more competitive with diversified services In addition, it would also bring more investment opportunities, creating jobs and raising incomes

2.1.2 The online fashion rental service

The increase in renting services, which can give many things a second life, has also contributed to the sharing economy Network-based rental service which can be the center of continuous development make save resources by sharing and protecting environment (Tu and Hu, 2018) In foreign countries, many online websites for clothing rental has been creating and developing

Rent the Runway (US), an online service that provides designer dresses and accessory rentals, was established since 2009 and has been operating for eleven years The company currently focuses on renting formal wear service for events such as banquets and weddings It offers clothes and accessories from the biggest names in fashion, such as Prabal Gurung, Self-Portrait, Brock Collection, Celine, Stella McCartney and Tory Burch, in addition to affordable lines like Reformation, Nike and Splendid The payment that is required for customers is around 10% of the original price of the clothing to rent formal wear And a monthly rental service was launched in 2017

A competitor to similar companies like Rent the Runway, which focuses on end fashion, the plus-sized service Gwynnie Bee, and others, Le Tote (US) allows users to borrow and wear unlimited items for $69 per month It was established in

high-2012 and has been operating for 8 years Current brands include Free People, BCB

Generation, Sam Edelman, House of Harlow, French Connection, Vince Camuto, and nearly 80 others The customers can keep their items as long as they want, return products and receive a new shipment, or purchase them for 20 to 50 percent off retail prices, given their secondhand nature

Dubbed the ―Airbnb of Australian fashion‖, The Volte is an Australian online marketplace that enables members to borrow and lend high-end designer clothing

It works similarly to community closet sharing sites although it focusses specifically

on high-end designer dresses, outerwear, handbags, and accessories with a recommended retail price of $100 Borrowers will find many exquisite garments from popular Australian brands such as Alice McCall, Alex Perry, Thurley, Nicola Finetti and Zimmerman from as little as $49 per item The general lend period is 4 days and dry cleaning‘s included in customer fee

Aircloset is one Japanese company renting out everyday clothes for women at a specific fee by ≦9,800 a month AirCloset began in February 2015 when the company realized what the fashion industry lacked a sustainable, recycling-based business model Its focus is on the Japanese boutique clothing market, and it sends three sets of clothing to subscribers every month (including tops, pants and skirts) for a fee Another project of AirCloset named ShareCloset that aimed at reducing apparel waste The company works with specific clothing brands to gather used garments from customers It subsequently uses AirCloset‘s experience and techniques to add these garments to the sharing service or recycle them as materials One Taiwan renting clothes company is AMAZE which was operated since 2016 The company currently offers more than 1200 styles and more than 5000 pieces of clothing It provides a variety price of online service options including NT$999, NT$1999, and NT$3999 Users can rent clothes today and receive them two days later Shipping is offered free of charge to provide the most convenient service to consumers If customers like a piece of clothing after renting, they can also buy it at cost

One of China‘s largest fashion rental platform is Ycloset which has 15 million registered users It was established in 2015 and has been operating for five years This company focuses on fashion sharing for women and it is engaged in the business of ―monthly dressing‖ Customers pay a monthly subscription rather than per item fee and are able to buy the clothing after they have rented it In 2019, H&M, the world‘s second-biggest fashion group, had teamed up with Chinese subscription rental platform Ycloset for its brand COS to try renting out clothes in the country as environmentally conscious consumers rein in purchases

The establishment and development of these online platforms are based on the benefits that fashion rental service brings For the textile industry, hiring clothes service has many significant economic benefits The fashion rental model earns revenue from rental fees and can be an alternative source of revenue for retailers in the industry (Rachel Botsman and Rogers, 2010; Perlacia, Duml and Saebi, 2017) For fashion rental companies, the main sources of costs stem from labor and website maintenance (Perlacia, Duml and Saebi, 2017) In the long run, they will be able to generate revenue by allowing the clothing items to be used and rented multiple times by different consumers with the frequent turnaround cycle Moreover, some fashion-rental and e-commerce companies charge for shipping and

laundry services Benjaafar et al.(2019) have identified that the rental platform is

most profitable when the owners and renters are balanced

Customers also get benefits from fashion rental services According to study of

Benjaafar et al (2019), the rental service improves consumer welfare and reduces

societal costs Without taking complete ownership, consumers can experience products for a chosen period by sharing in a small portion of the original price (Rachel Botsman and Rogers, 2010) Fashion is closely related to individuals' personalities and their external symbols such as status, uniqueness, or beauty Using fashion products is one of the ways to show off status and wealth (Yuan and Shen, 2019) In order to be considered fashionable, people must follow the fashion trends

that constantly changes (Yurchisin and Johnson, 2010; Armstrong et al., 2015)

Instead of purchasing luxurious products, people can access a taste of those products through renting services Hiring clothes facilitates conditions for consumers to always have new, diversified and fashionable apparel products that suit their needs (Balck and Cracau, 2015) without ever having a cluttered wardrobe Moreover, through renting, consumers avoid buying something that is only used just a few times

Despite the potential of the online fashion rental market, the knowledge regarding consumers' perceptions and factors affecting consumers' intentions to rent fashion items online is less Most existing studies on collaborative economy focus on house renting and car renting, with only a few that notice clothes hiring or sharing clothes Therefore, this research will discuss in more detail the issues related to factors affecting customer behavior in participating in online fashion rental service, while providing additional knowledge of this potential business model

2.2 The characteristics of generation Z (gen Z)

In the recent years, gen Z is becoming an interesting topic that is concerned by many authors (Ozkan and Solmaz, 2015; Abdullah, Mahadee Ismail and Albani, 2018b; Chicca and Shellenbarger, 2018; Schenarts, 2020) There are some discussions on the exact dates defining this generation, however, in general, Gen Z includes those born after 1995 This period coincidentally aligns with the approximate time when the World Wide Web appeared and became popular (Chicca and Shellenbarger, 2018) There are various names of this group currently used in the studies, including Generation Z, iGen, digital natives, net Generation, iGeneration, Gen Next, I Gen, Gen Tech, Post Gen, and Plurals (Turner, 2015; Seemiller and Grace, 2016; Jean M Twenge, 2017)

Gen Z has many outstanding and different characteristics compared to other groups that emphasized in the prior research (Igel and Urquhart, 2012; Jean M Twenge, 2017; Loveland, 2017; Schenarts, 2020) Firstly, this group's members are considered as true digital natives and the only generation raised exclusively with a technology influence They are avid consumers of technology and wallow in the

digital world with highly interactive Their daily lives are completely saturated with the digital environment Shatto and Erwin(2017) reported that the frequency of using mobile phone of gen Z is an average of 9 hours per day Secondly, Generation

Z desires convenience and immediacy They are quite pragmatic Having grown up

in the context of social, political, and economic uncertainty, this group is cautious and concerned with emotional, physical, and financial safety In addition, Jean M Twenge (2017) suggested that the common events and contextual factors experienced by gen Z have led to more practical, cautious, and skeptical youths When young people abandon TV and other traditional media, they replace it by using social media at very high frequency Hence, understanding how teenagers use social media throughout their shopping process is key to engaging them on the right platforms with the right message (Marianne Wilson, 2017) According to results of Bluecore survey, there are clear differences in the choices different generations make when using social media to learn about new products (Marketing Charts, 2016) 85% of Gen Z uses social media to learn about new products and 69% will visit a store based on the retailer's social media post In addition, figures show that 45% of young people use Instagram to find new products, followed by Facebook with 40% of users YouTube is also the platform of preference when it comes to shopping recommendations (Dara Fontein, 2019) Gen Z consumers are more likely than other groups to purchase an item due to: what their family or friends think; recommendations from YouTube; and comments on social media In addition, when shopping online, their interactions are higher, such as: chat with an online sales assistant; check in store for more information; ask friends‘ or relatives' opinions via social media, message or phone The findings of Morning Consult‘s Influencer Report show that 52% of Gen Z trusts influencers' advice about products or brands, while 82% of them trust their friends and family over any other source (Tracy Francis and Fernanda Hoefel, 2019)

2.3 Theory of planned behavior (TPB)

TPB has been adopted broadly in many studies that cover different research areas in

specific contexts It is a causal model to explain behavior and is considered as an extended model of TRA (Ajzen, 1991) According to TPB, a person‘s actual behavior is directly influenced by behavioral intention which is determined by attitude, subjective norm and perceived behavioral control toward performing the behavior (Wu and Chen, 2005) In other words, human behavior is shaped by three considerations: beliefs about the likely consequences and experiences associated with the behavior (behavioral beliefs), beliefs about the normative expectations and behaviors of significant others (normative beliefs), and beliefs about the presence of factors that may facilitate or impede performance of the behavior (control beliefs)

In their respective aggregates, behavioral beliefs produce a favorable or unfavorable attitude toward the behavior; normative beliefs result in perceived social pressure or subjective norm; and control beliefs give rise to perceived behavioral control or self-efficacy (Ajzen, 2010)

Attitude expresses the feeling of a person‘s favorable or unfavorable assessment regarding the behavior Furthermore, a favorable or unfavorable attitude is a direct influence on the strength of behavioral beliefs about the likely consequences or the past experience (Sohn and Kwon, 2020)

Subjective norm shows the perceived organizational or social pressure of a person regarding perform the behavior intention In another way, subjective norm is relative to normative beliefs about the expectations of other persons In many articles' suggestion, the dimension of normative belief should be decomposed into reference groups Taylor and P Todd (1995) decompose of the subjective norm into peer influence and superior influence seems justified in an organizational setting in which one‘s peers may be opposed towards specific behavior, whereas, at the same time, one‘s superior may be encouraging towards the behavior Bhattacherjee (2000) separated subjective norms into interpersonal influence and external influence When the potential adopters try to do something, they will look for the experience of the previous adopters (interpersonal influence) or consult the experts from the mass media in this field (external influence), so as to reduce the

uncertainty In this research, following the external factors which have more impact

on gen Z, subjective norm can be determined through three main variables: interpersonal influence, electronic word of mouth (EWOM) and influencers marketing

The restriction of TRA is to predict the behaviors of those with weak control Different from TRA, TPB includes perceived behavioral control that is the perception of the ease or difficulty of performing the behavior (Wu and Chen, 2005; Ulker-Demirel and Ciftci, 2020) The effects of attitude toward the behavior and subjective norm on intention are moderated by perception of behavioral control As

a general rule, the more favorable the attitude and subjective norm, and the greater the perceived control, the stronger should be the person‘s intention to perform the behavior in question (Ajzen, 2010)

2.4 Technology acceptance model (TAM)

Technology Acceptance Model (TAM) was introduced by Fred Davis in 1986 (Davis, Bagozzi and Warshaw, 1989) It is an adaptation of the theory of reasoned action (TRA) and mainly designed for modeling user acceptance of information technology This model hypothesizes that system use is directly determined by behavioral intention to use, which is in turn influenced by user‘s attitude toward using the system And, attitude is affected by perceived usefulness and perceived ease of use According to the defining of Davis, perceived usefulness reflects the users' belief that using a specific application system will enhance their job or life performance Besides, perceive ease of use can be defined as the degree to which the users expect the target system to be free of effort (Taylor and P A Todd, 1995) Both perceived ease of use and perceived usefulness which are the most important determinants of actual system use can be influenced by external variables (Wu and Chen, 2005) The main external factors are social factors, cultural factors and political factors Social factors include language, skills and facilitating conditions Political factors are mainly the impact of using technology in politics and political crisis

TAM is one of the most popular theories that is used widely to explain Information System usage Hence, many researchers have suggested the changes in the originally proposed model A new model called combined TAM‐TPB model was

built by Taylor and Todd (1995) Venkatesh et al.(2000) developed a new version

of TAM called TAM 2 which added new variables to the existing model Besides, TAM has been used to understand the acceptance of different types of information systems such as: eLearning systems, online shopping platform, online banking applications (Zhou, Dai and Zhang, 2007; Priyanka Surendran, 2012)

2.5 The framework and the research hypotheses

This study combines TPB and TAM to predict and analyze the factors that can affect the customers‘ willingness to engage in fashion rentals as the model below

Figure 1: Proposed Research Model

Subjective norms

Perceived behavioral control

Behavioral intention

of clothes renting

2.5.1 Perceived usefulness

Perceived usefulness is defined as ‗the degree to which a person believes that using

a particular technology will enhance his or her job performance‘ (Davis, Bagozzi and Warshaw, 1989) This means that the user has a perception of how useful the technology is performing in his/her job tasks On the other way, Davis, Bagozzi and Warshaw (1992) said that perceived usefulness refers to consumers‘ perceptions regarding the outcome of an experience This follows from the definition of the word useful: ―capable of being used advantageously.‖

As the results of some past TAM studies, perceived usefulness has a possible impact on enhancing user‘s attitude towards usage The effect of perceived usefulness on attitude has also been validated in many existing studies (Chen,

Gillenson and Sherrell, 2002) For examples: Fumei Weng et al (2018) found that

the attitude toward behavior was significantly affected by predicting usefulness in using multimedia teaching material for school teachers Teo (2010) conducted a study on pre-service teachers‘ attitudes toward computer use The results indicated that perceived usefulness significantly influences on attitude In line with other research, perceived usefulness plays important role in shaping attitude toward online airline tickets purchasing (Renny, Suryo Guritno and Hotniar Siringoringo, 2013) Therefore, this study postulates following hypothesis:

H1a: Perceived usefulness has a positive relationship with attitude regarding online fashion rental services

2.5.2 Perceived ease of use

Davis described perceived ease of use as ―the degree to which a person believes that using a particular system would be free of physical and mental effort‖ (Davis, Bagozzi and Warshaw, 1989) It also means a user‘s subjective perception of the effortlessness of a computer system This follows from the definition of the word

―ease‖: ―freedom from difficulty or great effort.‖

TAM posits that perceived ease of use has a direct positive effect on attitude toward using the system Complexity of one particular system will become the inhibitor that discourages the adoption of an innovation (Rogers, 1993) Many studies were conducted to validate TAM by using perceived ease of use and perceived usefulness

as two independent variables and attitude towards behavior as the dependent variable (Teo, 2010; Renny, Suryo Guritno and Hotniar Siringoringo, 2013;

Juniwati, 2014; Fumei Weng et al., 2018) The results show that perceived

usefulness is significantly correlated with attitude As the same way, perceived ease

of use also has positive impacts on attitude Based on the above arguments, the proposed hypothesis is:

H1b: Perceived ease of use has a positive relationship with attitude regarding online fashion rental services

2.5.3 Interpersonal influence

As mention above, Interpersonal is one of the dimensions that has intensive impact

on subjective norms (Bhattacherjee, 2000) Interpersonal behavior is referred to the change in one's behavior due to others' feelings or opinions This influence might reflect the compliance and acceptance with others' expectation Before making a decision, Bhattacherjee (2000) argued that potential adopters solicit opinions from peers who already know about the characteristics and worthiness of a service Interpersonal sources create important influences, especially on decisions involving uncertainty (Fenech and O‘Cass, 2001) Besides, the strong influence of proximate people was posited and emphasized (Johnson, 2004), such as friends, family and co-

workers (Hsu et al., 2006; Hung, Chang and Yu, 2006) Regarding online fashion

rentals, Tu and Hu (2018) found that the positive relationship between interpersonal influence and subjective norms was significant Hence, this study assumes that:

H2a: Interpersonal influence has a positive relationship with attitude regarding online fashion rental services

2.5.4 Electronic word of mouth (E-WOM) credibility

Based on previous studies, it shows that word of mouth (WOM) through social media which means face-to-face communication among people plays an important role in influencing consumers‘ decision making (Brown and Reingen, 1987; Mazzarol, Sweeney and Soutar, 2007) It allows consumers to communicate in an unbiased manner regarding products or services in a platform believed to be non-related to an organization With the development of internet, it had established a more universal and less personal kind of WOM which is electronic word of mouth (E- WOM) Hennig-Thurau and Walsh (2003) defined E-WOM as comments either positive or negative which are made by customers regarding product or service to an amount of people through the Internet E-WOM is also considered to be an important platform that allows consumers to communicate and transfer their thoughts to others (Godes and Mayzlin, 2004) In addition, E-WOM is also considered to be more effective when compared to traditional word of mouth as it is more convenient and it has the ability to achieve a higher reach

WOM which can be considered in terms of peers influence generated by workers, relatives or friends has positive relationship with subjective norms (Bhattacherjee, 2000; Teo, 2010) Numerous studies have validated the significant influence of word of mouth on subjective norm (Bhattacherjee, 2000; Md Husin, Ismail and Ab Rahman, 2016) In addition, WOM is also said to generate the subjective norm construct wherever consumer considers technology adoption (Palka, Pousttchi and Wiedemann, 2009) Hence, some authors also suggest the influence of E-WOM on subjective norms (Jalilvand and Samiei, 2012; Doma, Elaref and Abo Elnaga, 2015; Goh, 2015) Besides, Chatterjee (2001) and Fong and Burton (2008) discussed more details in terms of the differences between E-WOM and WOM They argued that E-WOM is more effective than WOM due to the ease

co-of use and the width co-of range Adopting these articles, the study suggests the hypothesis:

H2b: E-WOM credibility has a positive relationship with subjective norms regarding online fashion rental services

2.5.5 Influencer marketing (KOLs)

Brown (2013) defines that influencer marketing is ―Typically a noncustomer or business incentivised to recommend/create content about a business brand or product‖ Another definition which Brown and Hayes (2008) gave is that the word

―Influence‖ can be broadly defined as the power to affect a person, thing or course

of events Influencer marketing can appear as an entirely new marketing strategy

As previous studies, it may affect the subjective norm of individuals (De Koning, 2018) Subjective norm which also is social influence means ―the person‘s perception that most people who are important to him or her think he/she should or should not perform the behavior in question‖

In addition, influencer marketing can be seen as a virtual word of mouth but it works differently than word of mouth A company uses influencers to reach consumers instead of family or friends, by providing the agreed messages or activities between the company and influencer Consumers are much more likely to positively perceive and react to a message that comes from a trusted personal over a sponsored post that comes from a company (Woods, 2016; Wroblewski, 2017) Especially, in fashion industry, influencers who often have a high number of followers on social networks can be useful for brands to attract consumers The research focuses on gen Z who is significantly and directly affected by famous people or influencers Hence, the following hypothesis is proposed:

H2c: Influencer marketing has a positive relationship with subjective norms regarding online fashion rental services

2.5.6 Attitude toward behavior

Following the results of TRA or TPB research, attitude is one of the major determinants that shape behavioral intention (Ajzen, 1991) Attitude refers to a person‘s assessment of human, objects and goods (Blackwell R, Miniard P and

Engel J, 2006) This involves favorable or unfavorable assessment, emotional feelings, and behavioral propensity (De Koning, 2018) Furthermore, by TPB model, attitude toward behavior is explained as the degree whereby an individual makes a positive or negative evaluation towards the behavior in question (Ajzen, 1991) Hence, it can be said that as attitudes are more favorable toward the behavior, a person‘s intention to execute the behavior will be stronger A further commonplace is that attitudes have cognitive components, affective components, and behavioral components In which, the behavioral component is central to research's concern here, following the argument of Ajzen (1991) : ―The ability of attitudes to predict behavioral intentions or overt behavior continues to be a major focus of theory and research‖

The positive impacts of attitude on behavioral intention are explored and proved in many studies in different fields (Fusilier, Harrison and Worley, 1996; Ajzen, 2010; Jalilvand and Samiei, 2012; Juniwati, 2014; Chew and Abdul Adis, 2018) In particular: Fusilier, Harrison and Worley (1996) suggested that attitude is positively related to the behavioral intention to provide AIDS care Another report showed that positive attitude leads high behavioral intention of waste management technology at students (Siahaan, 2018) Regarding to renting clothes, attitude also is one of the main determinants that positive influences on intention to hire (Tu and

Hu, 2018; Lee and Chow, 2020) This study suggests the hypothesis:

H3: Attitude toward behavior has a positive relationship with behavioral intention regarding online fashion rental services

2.5.7 Subjective norms

Subjective norm is the second determination of intention in the TPB model Ajzen (1991) said that it is the perception of social pressures to undertake or not to undertake a given behavior Another component towards subject norms is normative belief, which defines the perceptions of an individual towards the views regarding his/her act generated by a person believed to be important to that individual The

TPB model shows that wherever the stronger the drive to adhere to social pressure, the role of social pressure is more important (Mathieson, 1991) Furthermore, Taylor and P Todd (1995) also recorded the subjective norms as a basis for

intention Besides, Venkatesh et al (2003) concluded that subjective norm

originated through social influences is crucial to ascertain users‘ intention towards the acceptance and usage of technology

Many other studies also indicate that subjective norm has impact on the intention For instant: The finding of a research showed that subjective norm was significantly and positively correlated with learners' behavioral intention in using e-learning (Yau and Ho, 2015) Shin and Hancer (2016) adopted the extended TPB model of Ajzen

in their study and indicated that subjective norm in the standard model was supported Another article also analyzed the specific role of two types of subjective norms in forming the intention to purchase green food (Ham, Jeger and Ivković, 2015) Hence, this study assumes that subjective norm has positive effects on the behavioral intention of clothes renting

H4: Subjective norm has a positive relationship with behavioral intention regarding online fashion rental services

2.5.8 Perceived behavioral control

Ajzen introduced perceived behavioral control into his theory of planned behavior

as a determinant behavioral intention (Ajzen, 1991) Perceived behavioral control means an individual‘s perception regarding the ease or difficulty in undertaking the behavior In addition, it reflects on past experiences and also forecasts about impediments or consequences (Ajzen, 2002) Furthermore, perceived behavioral control is combined of two different factors namely control beliefs and perceived facilitation (De Koning, 2018) Control belief is an individual‘s belief regarding to the self-availability of skills, resources and opportunities Perceived facilitation relates to the accessibility of time, money or other specific resources for certain behavior (Tu and Hu, 2018)

TPB suggested that perceived behavioral control directly affects the intention to perform a behavior and also the actual performance of that behavior as compared to the extent of the actual behavioral control Like Ajzen's theory of planned behavior, most psychosocial theories of health behavior have incorporated perceived behavioral control as a major determinant of intention to engage in health behavior (K Wallston, 2001) This study also proves the influence of perceived behavioral control on behavioral intention by proposed hypothesis:

H5: Perceived behavioral control has positive relationship with behavioral intention regarding online fashion rental services

2.5.9 Behavioral intention

Behavioral intention reflects the tendency for which a person wants to take a specific action, and it can be measured by a person‘s willingness to have an experience or the effort of person makes to take an action According to TPB model

of Ajzen, it is pointed out that behavioral intention is the best way to predict individual behavior (Ajzen, 1991) In other words, when people have stronger intention to take some actions, then the probability of taking the action will be higher This study proposes that three main factors: attitude, subjective norm, and perceived behavioral control have a significant positive correlation with behavioral intention of customer to engage in online renting clothes service

CHAPTER 3: RESEARCH METHODOLOGY

This chapter is divided into 5 sections from 3.1 to 3.5 The first section shows the research procedure which involves each step taken in the analysis The using of survey as a quantitative method is identified in the next section After that, section 3.3 shows the designing of questionnaire and pilot testing before practical survey Then, information about sample size and how to collect data is presented in section 3.4 The last section gives the basic knowledge about the data analysis methods and its evaluation standards that are used in the study

3.1 Research procedure

This research aims to analyze the knowledge about online clothing rental industry

as well as its opportunities and discuss the factors affecting Gen Z‘s behavioral intention to rent clothes According to the aforesaid literature review, the research procedure of this research is constructed as shown in figure below:

Figure 2: Research procedure

TPB and TAM model were used to discuss the factors affecting customer’s intention to rent clothes online

- Summarize the related research

- Identify the research objectives

Review the prior studies and

develop research

1 Get the knowledge related to

TPB, TAM, sharing economy, online fashion rental, gen Z

2 Proposed the theoretical

structure and research hypotheses

1 Plan to do questionnaire and develop questions based on previous studies

2 Advise with the supervisors for final questionnaire and doing pilot test

3 Identify sample size

4 Collect data and clear it before analyzing

Import data and analyze by SPSS26 and AMOS20 software

Conclusions, Limitations and Suggestions for future researchs

3.2 Survey as a quantitative research method

In this study, quantitative research method is used to quantify the problem by way

of generating numerical data

The survey refers to via a set of questions designed to find out and prove relationships between variables The most noticeable characteristics of the survey is that data of multiple cases are collected at one point of time (De vaus, 2001; Bryman and Bell, 2007) One of the most advantages of the survey is its reasonable costs to collect data within a relatively short period of time However, if the questionnaire is not carefully designed, the misunderstanding of respondent can be a major problem (Johnson and Turner, 2007)

The survey consists of different stages The first phase is to state the problems that will be examined by the studies At this stage, main concepts of the study are clarified before hypotheses are developed and conceptual framework is built Secondly, a pilot test is advisable to ensure the questionnaire is in the best quality concerning its content, its length, and its understandability to target respondents Thirdly, this is followed by sample plan that allows the researcher to identify a minimum sample size for the study before the questionnaire is officially delivered

on a large scale According to Hair et al (2014) the minimum of sample size is to

have at least five times as many observations as the number of items in questionnaire to be analyze The next phase is to clean the data before certain techniques or methods of data analysis are implemented Then, research findings are drawn Importantly, the credibility of research findings is significantly influenced

by two vital aspects of survey design namely reliability and validity

3.3 Questionnaire design and pilot test

3.3.1 Definition of items

The theoretical structure model of this study consists of 8 hypotheses, and the variables of each hypothesis are defined and operated according to relevant literature The questionnaire items of variables are appropriately modified regarding